Fast growth of the pervasive computing and handheld/communication industry has generated exploding demand for electrical devices including high capacity nonvolatile solid-state data storage devices. Current devices using flash memory have several drawbacks such as slow access speed (˜ms write and ˜50−100 ns read), limited endurance (˜103−104 programming cycles), and the integration difficulty in system-on-chip (SoC). Flash memory (NAND or NOR) also faces significant scaling problems at 32 nm node and beyond.
Magneto-resistive or magnetic random access memory (MRAM) is a promising candidate for future memory. One basic component of MRAM is a magnetic tunneling junction (MTJ). Data storage is realized by switching the resistance of MTJ between a high-resistance state and a low-resistance state. MRAM switches the MTJ resistance by using a current induced magnetic field or current induced spin torque transfer to switch the magnetization of the MTJ. In operation, the MRAM can be read by measuring the resistance and inferring the magnetization state of the MTJ. Electrical devices including those incorporating MRAM can be dependent on power utilization. The need exists for more efficient ways to monitor the power utilization of an electrical device.
As the MTJ size shrinks, magnetization fluctuation signature increases as the MTJ and MRAM devices scale down in size. Quantifying the magnetization fluctuation signature at nanometer length scale and monitoring power use is a challenge.